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Multi-objective Emergency Scheduling for Geological Disasters

Author

Listed:
  • Wan Fang

    (China University of Geosciences)

  • Guo Haixiang

    (China University of Geosciences
    China University of Geosciences
    Xi’an University of Finance and Economics)

  • Li Jinling

    (China University of Geosciences)

  • Gu Mingyun

    (China University of Geosciences)

  • Pan Wenwen

    (China University of Geosciences)

Abstract

Because of the specific time and distance constraints, emergency management departments usually build multiple depots (resource centers) to serve the widely dispersed customers (disaster areas), to more effectively fulfill customer demand, and deal with the changing road conditions in real time. Therefore, research on multi-depot dynamic emergency dispatch can be of significant value to effective disaster operations. In this paper, a multi-objective multi-depot and multi-type dynamic vehicle routing problem model is established that minimizes total distance and priority errors and considers secondary disasters, damaged roads, the limited vehicle number at the various depots, and the different vehicle capacities. To solve this model, a hybrid ant colony optimization based on the circumcenter of the polygon formed by depots is proposed. Real landslides disaster data from Hubei province and two kinds of benchmark instances test the performance of the proposed algorithm. After detailed experimental comparisons, the competitive performance of the proposed algorithm is verified.

Suggested Citation

  • Wan Fang & Guo Haixiang & Li Jinling & Gu Mingyun & Pan Wenwen, 2021. "Multi-objective Emergency Scheduling for Geological Disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(2), pages 1323-1358, January.
    • Handle: RePEc:spr:nathaz:v:105:y:2021:i:2:d:10.1007_s11069-020-04356-3
    DOI: 10.1007/s11069-020-04356-3
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    References listed on IDEAS

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    1. Siquan Yang & Haixia He & Weitao Chen & Lizhe Wang, 2018. "Direct tangible damage assessment for regional snowmelt flood disasters with HJ-1 and HR satellite images: a case study of the Altay region, northern Xinjiang, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(3), pages 1099-1116, December.
    2. Shinyoung Kwag & Daegi Hahm, 2020. "Multi-objective-based seismic fragility relocation for a Korean nuclear power plant," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 3633-3659, September.
    3. Schmidt, M. & Schöbel, Anita & Thom, Lisa, 2019. "Min-ordering and max-ordering scalarization methods for multi-objective robust optimization," European Journal of Operational Research, Elsevier, vol. 275(2), pages 446-459.
    4. Xiaowen Xiong & Fan Zhao & Yundou Wang & Yapeng Wang, 2019. "Research on the Model and Algorithm for Multimodal Distribution of Emergency Supplies after Earthquake in the Perspective of Fairness," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-12, January.
    5. B Yu & Z-Z Yang & J-X Xie, 2011. "A parallel improved ant colony optimization for multi-depot vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 183-188, January.
    6. Sarat Kumar Das & Ranajeet Mohanty & Madhumita Mohanty & Mahasakti Mahamaya, 2020. "Multi-objective feature selection (MOFS) algorithms for prediction of liquefaction susceptibility of soil based on in situ test methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(2), pages 2371-2393, September.
    7. Chi-Hsiang Wang & John D. Holmes, 2020. "Exceedance rate, exceedance probability, and the duality of GEV and GPD for extreme hazard analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 102(3), pages 1305-1321, July.
    8. Kai Wang & Haiqing Hao & Shuguang Jiang & Zhengyan Wu & Chuanbo Cui & Hao Shao & Weiqing Zhang, 2019. "Escape route optimization by cellular automata based on the multiple factors during the coal mine disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(1), pages 91-115, October.
    9. Yu, Bin & Yang, Zhong-Zhen & Yao, Baozhen, 2009. "An improved ant colony optimization for vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 196(1), pages 171-176, July.
    10. Gao, Shangce & Wang, Yirui & Cheng, Jiujun & Inazumi, Yasuhiro & Tang, Zheng, 2016. "Ant colony optimization with clustering for solving the dynamic location routing problem," Applied Mathematics and Computation, Elsevier, vol. 285(C), pages 149-173.
    11. Baozhen Yao & Chao Chen & Xiaolin Song & Xiaoli Yang, 2019. "Fresh seafood delivery routing problem using an improved ant colony optimization," Annals of Operations Research, Springer, vol. 273(1), pages 163-186, February.
    12. Abbasali Ebrahimian & Hossein Babaei & Ali Fakhr-Movahedi, 2020. "Factors associated with unnecessary requests for an ambulance by non-traumatic patients after the acute earthquake responding phase: a qualitative content analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(2), pages 2009-2020, September.
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